We nowcast world trade using machine learning, distinguishing between tree-based methods (random forest, gradient boosting) and their regression-based counterparts (macroeconomic random forest, linear gradient boosting). While much less used in the literature, the latter are found to outperform...

Countries have employed a variety of non-pharmaceutical interventions (NPIs) in order to curtail the COVID-19 pandemic. However, the success of individual measures in reducing the number of infections remains controversial. This paper exploits a panel data set of 107 countries to estimate the...

We review and construct consistent in-sample specification and out-of-sample model selection tests on conditional distributions and predictive densities associated with continuous multifactor (possibly with jumps) and (non)linear discrete models of the short term interest rate. The results of...

There are over 3 billion searches globally on Google every day. This report examines whether Google search queries can be used to predict the present and the near future unemployment rate in Finland. Predicting the present and the near future is of interest, as the official records of the state...

Today's economy is characterized by increased competition, faster product development and increased product differentiation. As a consequence product lifecycles become shorter and demand patterns become more volatile which especially affects the retail industry. This new situation imposes...

Scientific, political and bureaucratic elites use epistemic practices like “big data analysis” and “web scraping” to create representations of the citizenry and to legitimize policymaking. I develop the concept of “demos scraping” for these practices of gaining information about...

KI-Modelle und Machine-Learning-Anwendungen halten Einzug in die alltägliche Praxis von Unternehmen und können mitbestimmt werden. Um die Interessen und Rechte der Beschäftigten zu berücksichtigen und zu schützen, sollten die aktuellen Regelungen in betrieblichen IT-Vereinbarungen...

Machine Learning ist ein Forschungsfeld mit großen Potenzialen und weitreichenden Anwendungspotenzialen. Big Data kann dabei als Enabler angesehen werden, da große und qualitativ hochwertige Daten stets die Grundlage für erfolgreiche Machine Learning-Algorithmen und -Modelle darstellen....

Computational methods to gauge investor sentiment from commonly used online data sources that rely on machine learning classifiers and lexicons have shown considerable promise, but suffer from measurement and classification errors. In our work, we develop a simple, direct and unambiguous...

We provide new evidence on the extent to which the demand for cigarettes is derived from the demand for weight control (i.e. weight loss or avoidance of weight gain). We utilize nationally representative data that provide the most direct evidence to date on this question: individuals are...